An Energy Efficient Resource Allocation Scheme Based on Cloud-Computing in H-CRAN

Compared with the cloud radio access network (C-RAN), heterogeneous cloud radio access network (H-CRAN) with the high-power node (HPN) entity which separates the control and broadcast functionalities from the baseband processing unit (BBU) pool. It makes the user access, resource allocation, load balancing more flexible, which also makes the intra-layer interference and inter-layer interference more complex. Therefore, the heavy inverse operations for dense matrixes and the complicated power allocation algorithms in beamforming perform large floating-point calculations per second (FLOPS) in BBU pool. As frequency resources grow scarcer, green communication with high energy efficiency and low carbon emissions has raised significant concerns. In this paper, we focus on the energy efficiency (EE) advantages achieved by selectively cooperative transmission and associated power consumption model. A joint channel matrix sparseness and normalized water-filling resource allocation algorithm is proposed and formulated to improve energy efficiency at different user density through mathematical derivation. By reducing the computation complexity of cooperative transmission, the proposed scheme decreases the digital baseband power consumption, which is more adaptable for tidal phenomenon. Simulation results show that the proposed algorithm can effectively reduce the energy consumption of baseband and improve the energy efficiency of the system.